Human recognition has become an important topic as the need and investments for security applications grow continuously. Biometrics enable reliable and efficient identity management systems by using physical and behavioral characteristics of the subjects that are permanent, universal and easy to access. This is why, the topic of biometrics attracts higher attention today. Numerous biometric systems exist which utilize various human characteristics. Among all biometrics traits, face recognition is advantageous in terms of accessibility and reliability. It allows identification at relatively high distances for unaware subjects that do not have to cooperate. In this dissertation, two challenges in face recognition are analyzed. The first one is face spoofing. Initially, spoofing in face recognition is explained together with the countermeasure techniques that are proposed for the protection of face recognition systems against spoofing attacks. The second challenge explored in this thesis ...

Absolute security does not exist: given funding, willpower and the proper technology, every security system can be compromised. However, the objective of the security community should be to develop such applications that the funding, the will, and the resources needed by the attacker to crack the system prevent him from attempting to do so. This Thesis is focused on the vulnerability assessment of biometric systems. Although being relatively young compared to other mature and long-used security technologies, biometrics have emerged in the last decade as a pushing alternative for applications where automatic recognition of people is needed. Certainly, biometrics are very attractive and useful for the final user: forget about PINs and passwords, you are your own key. However, we cannot forget that as any technology aimed to provide a security service, biometric systems are exposed to external attacks which ...

The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. However, the inherent vulnerability and fragility of machine learning architectures pose new serious security threats, hindering the use of these tools in security-oriented applications, and, among them, multimedia forensics. The analysis of the security of machine learning-based techniques in the presence of an adversary attempting to impede the forensic analysis, and the development of new solutions capable to improve the security of such techniques is then of primary importance, and, recently, has marked the birth of a new discipline, named Adversarial Machine Learning. By focusing on Image Forensics and ...

The achievement of perfect security is out of the question. Even if we are not yet aware of them, every security aimed technology has weaknesses which attackers can exploit in order to circumvent the system. We should hence direct our efforts to the development of applications whose security level make it infeasible for computationally bound attackers to break the systems. This Thesis is focused on improving the security and privacy provided by biometric systems. With the increased need for reliable and automatic identity verification, biometrics have emerged in the last decades as a pushing alternative to traditional authentication methods. Certainly, biometrics are very attractive and useful for the general public: forget about PINs and passwords, you are your own key. However, the wide deployment of biometric recognition systems at both large-scale applications (e.g., border management at European level or national ...

This thesis has two main parts. The first part deals with security and privacy analysis of biometric hashing. The second part introduces a method for fixed-length feature vector extraction and hash generation from fingerprint minutiae. The upsurge of interest in biometric systems has led to development of biometric template protection methods in order to overcome security and privacy problems. Biometric hashing produces a secure binary template by combining a personal secret key and the biometric of a person, which leads to a two factor authentication method. This dissertation analyzes biometric hashing both from a theoretical point of view and in regards to its practical application. For theoretical evaluation of biohashes, a systematic approach which uses estimated entropy based on degree of freedom of a binomial distribution is outlined. In addition, novel practical security and privacy attacks against face image hashing ...

Voice biometric systems use automatic speaker verification (ASV) technology for user authentication. Even if it is among the most convenient means of biometric authentication, the robustness and security of ASV in the face of spoofing attacks (or presentation attacks) is of growing concern and is now well acknowledged by the research community. A spoofing attack involves illegitimate access to personal data of a targeted user. Replay is among the simplest attacks to mount - yet difficult to detect reliably and is the focus of this thesis. This research focuses on the analysis and design of existing and novel countermeasures for replay attack detection in ASV, organised in two major parts. The first part of the thesis investigates existing methods for spoofing detection from several perspectives. I first study the generalisability of hand-crafted features for replay detection that show promising results ...

Visual and audio contents always played a key role in communications, because of their immediacy and presumed objectivity. This has become even more true in the digital era, and today it is common to have multimedia contents stand as proof of events. Digital contents, however, are also very easy to manipulate, thus calling for analysis methods devoted to uncover their processing history. Multimedia forensics is the science trying to answer questions about the past of a given image, audio or video file, questions like “which was the recording device?", or “is the content authentic?". In particular, authenticity assessment is a crucial task in many contexts, and it usually consists in determining whether the investigated object has been artificially created by splicing together different contents. In this thesis we address the problem of splicing detection in the three main media: image, ...

This dissertation studies soft biometrics traits, their applicability in different security and commercial scenarios, as well as related usability aspects. We place the emphasis on human facial soft biometric traits which constitute the set of physical, adhered or behavioral human characteristics that can partially differentiate, classify and identify humans. Such traits, which include characteristics like age, gender, skin and eye color, the presence of glasses, moustache or beard, inherit several advantages such as ease of acquisition, as well as a natural compatibility with how humans perceive their surroundings. Specifically, soft biometric traits are compatible with the human process of classifying and recalling our environment, a process which involves constructions of hierarchical structures of different refined traits. This thesis explores these traits, and their application in soft biometric systems (SBSs), and specifically focuses on how such systems can achieve different goals ...

Computer vision-based analysis of human facial video provides information regarding to expression, diseases symptoms, and physiological parameters such as heartbeat rate, blood pressure and respiratory rate. It also provides a convenient source of heartbeat signal to be used in biometrics and forensics. This thesis is a collection of works done in five themes in the realm of computer vision-based facial image analysis: Monitoring elderly patients at private homes, Face quality assessment, Measurement of physiological parameters, Contact-free heartbeat biometrics, and Decision support system for healthcare. The work related to monitoring elderly patients at private homes includes a detailed survey and review of the monitoring technologies relevant to older patients living at home by discussing previous reviews and relevant taxonomies, different scenarios for home monitoring solutions for older patients, sensing and data acquisition techniques, data processing and analysis techniques, available datasets for ...

In this doctoral dissertation, we principally explore the use of the temporal information available in video sequences for person and gender recognition; in particular, we focus on the analysis of head and facial motion, and their potential application as biometric identifiers. We also investigate how to exploit as much video information as possible for the automatic recognition; more precisely, we examine the possibility of integrating the head and mouth motion information with facial appearance into a multimodal biometric system, and we study the extraction of novel spatio-temporal facial features for recognition. We initially present a person recognition system that exploits the unconstrained head motion information, extracted by tracking a few facial landmarks in the image plane. In particular, we detail how each video sequence is firstly pre-processed by semiautomatically detecting the face, and then automatically tracking the facial landmarks over ...

The generation and manipulation of digital images is made simple by widely available digital cameras and image processing software. As a consequence, we can no longer take the authenticity of a digital image for granted. This thesis investigates the problem of protecting the trustworthiness of digital images. Image authentication aims to verify the authenticity of a digital image. General solution of image authentication is based on digital signature or watermarking. A lot of studies have been conducted for image authentication, but thus far there has been no solution that could be robust enough to transmission errors during images transmission over lossy channels. On the other hand, digital image forensics is an emerging topic for passively assessing image authenticity, which works in the absence of any digital watermark or signature. This thesis focuses on how to assess the authenticity images when ...

This thesis investigates the practical adaption of iris biometrics on smartphones. Iris recognition is a mature and widely deployed technology which will be able to provide the high security demanded by next generation smartphones. Practical challenges in widely adopting this technology on smartphones are identified. Based on this, a number of design strategies are presented for constraint free, high performing iris biometrics on smartphones. A prototype, smartphone form factor device is presented to be used as a front-facing camera. Analysis of its optical properties and iris imaging capabilities shows that such a device with improved optics and sensors could be used for implementing iris recognition in the next generation of smartphones. A novel iris liveness detection is presented to prevent spoofing attacks on such a system. Also, the social impact of wider adoption of this technology is discussed. Iris pattern ...

As biometrics gains popularity and proliferates into the daily life, there is an increased concern over the loss of privacy and potential misuse of biometric data held in central repositories. The major concerns are about i) the use of biometrics to track people, ii) non-revocability of biometrics (eg. if a fingerprint is compromised it can not be canceled or reissued), and iii) disclosure of sensitive information such as race, gender and health problems which may be revealed by biometric traits. The straightforward suggestion of keeping the biometric data in a user owned token (eg. smart cards) does not completely solve the problem, since malicious users can claim that their token is broken to avoid biometric verification altogether. Put together, these concerns brought the need for privacy preserving biometric authentication methods in the recent years. In this dissertation, we survey existing ...

Automatic speaker recognition is the use of a machine to identify an individual from a spoken sentence. Recently, this technology has been undergone an increasing use in applications such as access control, transaction authentication, law enforcement, forensics, and system customisation, among others. One of the central questions addressed by this field is what is it in the speech signal that conveys speaker identity. Traditionally, automatic speaker recognition systems have relied mostly on short-term features related to the spectrum of the voice. However, human speaker recognition relies on other sources of information; therefore, there is reason to believe that these sources can play also an important role in the automatic speaker recognition task, adding complementary knowledge to the traditional spectrum-based recognition systems and thus improving their accuracy. The main objective of this thesis is to add prosodic information to a traditional ...

Cryptography and biometrics have been identified as two of the most important aspects of digital security environment. For various types of security problems the merging between cryptography and biometrics has led to the development of Bio crypt technology. The new technology suffers from several limitations and this thesis, addresses the biometric information quality and the security weakness of cryptography. In many applications fingerprint has been chosen as a core of bio crypt combined technology due to it’s maturity in terms of availability, uniqueness, permanence, feasibility, ease of use and acceptance. Fingerprint has been studied from the point of view of information strength to suitability to the cryptographic requirement. The factors relating to generating and constructing combined bio crypt key such as biometric image validity, quality assessment and distinct feature extraction are studied to avoid corruptness of the source biometric images. ...